Many problems in image analysis, digital processing and shape optimization are expressed as variational prob- lems and involve the discritization of laplacians. Indeed, PDEs containing Laplace-Beltrami operator arise in surface fairing, mesh smoothing, mesh parametrization, remeshing, feature extraction, shape matching, etc. The discretization of the laplace-Beltrami operator has been widely studied, but essentially in the plane or on triangu- lated meshes. In this paper, we propose a digital Laplace-Beltrami operator, which is based on the heat equation described by BELKIN et al (2008) and adapted to 2D digital curves. We give elements for proving its theoretical convergence and present an experimental evaluation that confirms its convergence property.

This paper presents a multilevel analysis of 3D shapes based on their medial axes. Such an analysis is important for many applications including shape comparison, editing, and compression. We propose an algorithm to compute a 3D generalization of a skeleton-based salience measure in 2D, the weighted
extended distance function (WEDF), and use it for robust, unsupervised shape decomposition into a hierarchy of parts.

Deep Partitioned Shadow Volumes Using Stackless and Hybrid Traversals

F. Mora1, J. Gerhards1, L. Aveneau2, and D. Ghazanfarpour1

1 University of Limoges2 University of Poitiers

Papier déjà publié | Eurographics Symposium on Rendering 2016

Computing accurate hard shadows is a difficult problem in interactive rendering. Previous methods rely either on Shadow Maps or Shadow Volumes. Recently Partitioned Shadow Volumes (PSV) has been introduced. It revisits the old Shadow Volumes Binary Tree Space Partitioning algorithm, leading to a practicable and efficient technique. In this article, we analyze the PSV query algorithm and identify two main drawbacks: First, it uses a stack which is not GPU friendly; its size must be small enough to reduce the register pressure, but large enough to avoid stack overflow. Second, PSV struggles with configurations involving significant depth complexity, especially for lit points. We solve these problems by adding a depth information to the PSV data structure, and by designing a stackless query. In addition, we show how to combine the former PSV query with our stackless solution, leading to a hybrid technique taking advantage of both. This eliminates any risk of stack overflow, and our experiments demonstrate that these improvements accelerate the rendering time up to a factor of 3.

Surface derivatives computation using Fourier Transform

Yohann Béarzi1, Julie Digne1

1 LIRIS CNRS UMR 5205 - Université Lyon 1

Papier original j•FIG 2016

We present a method for computing high order derivatives on a smooth surface at a point p by analyzing the vibrations of the surface along circles in the tangent plane, centered at p. By computing the Discrete Fourier Transform of the deviation of S from the tangent plane restricted to those circles, a linear relation between the Fourier coefficients and the derivatives can be expressed. Thus, given a smooth scalar field defined on the surface, all its derivatives at p can be computed simultaneously. The originality of this method is that no direct derivation process is applied to the data. Instead, integration is performed through the Discrete Fourier Transform, and the result is expressed as a one dimensional polynomial. We derive two applications of our framework namely normal correction and curvature estimation which we demonstrate on synthetic and real data.

Projective texturing is a commonly used image based rendering technique that enables the synthesis of novel views from the blended reprojection of nearby views on a coarse geometry proxy approximating the scene. When scene geometry is inexact, aliasing artefacts occur. This introduces disturbing artefacts in applications such as street-level immersive navigation in mobile mapping imagery, since a pixel-accurate modelling of the scene geometry and all its details is most of the time out of question. The filtered blending approach applies the necessary 1D low-pass filtering on the projective texture to trade out the aliasing artefacts at the cost of some radial blurring. This paper proposes extensions of the filtered blending approach. Firstly, we introduce Integral Radial Images that enable constant time radial box filtering and show how they can be used to apply box-filtered blending in constant time independently of the amount of depth uncertainty. Secondly, we show a very efficient application of filtered blending where the scene geometry is only given by a loose depth interval prior rather than an actual geometry proxy. Thirdly, we propose a silhouette-aware extension of the box-filtered blending that not only account for uncertain depth along the viewing ray but also for uncertain silhouettes that have to be blurred as well.

It is well known that rational quadratic Bézier curves define conics. The use of massic points permits one to define a semi-conic in the Euclidean plane. Moreover, from a given quadratic Bézier curve, we determine the properties of the underlying conic using only one theorem which leads to a very simple program.

Implicit-based Secondary Motion for Character Animation

Valentin Roussellet1, Nicolas Mellado1 & Loïc Barthe1

1 IRIT - Université de Toulouse

Papier original j•FIG 2016

Generating secondary motion effects in interactive skinning techniques remains a challenging open problem hindering the realism of digital animated content. In this paper, we show that anatomic implicit models can be efficiently included in the implicit skinning framework for modeling complex secondary motions in real time.

Session 5

Jeudi 01 déc. 09:15 - 10:55

Modératrice : Céline Loscos

Perceptual Effect of Shoulder Motions on Crowd Animations

Ludovic Hoyet1, Anne-Hélène Olivier2, Richard Kulpa2, Julien Pettré1

1 Inria 2 Univ. Rennes

Papier déjà publié | SIGGRAPH 2016

A typical crowd engine pipeline animates numerous moving characters according to a two-step process: global trajectories are generated by a crowd simulator, whereas full body motions are generated by animation engines. Because interactions are only considered at the first stage, animations sometimes lead to residual collisions and/or characters walking as if they were alone, showing no sign to the influence of others. In this paper, we investigate the value of adding shoulder motions to characters passing at close distances on the perceived visual quality of crowd animations (i.e., perceived residual collisions and animation naturalness). We present two successive perceptual experiments exploring this question where we investigate first, local interactions between two isolated characters, and second, crowd scenarios. The first experiment shows that shoulder motions have a strong positive effect on both perceived residual collisions and animation naturalness. The second experiment demonstrates that the effect of shoulder motions on animation naturalness is preserved in the context of crowd scenarios, even though the complexity of the scene is largely increased. Our general conclusion is that adding secondary motions in character interactions has a significant impact on the visual quality of crowd animations, with a very light impact on the computational cost of the whole animation pipeline. Our results advance crowd animation techniques by enhancing the simulation of complex interactions between crowd characters with simple secondary motion triggering techniques.

We propose a method to reconstruct 3D developable surfaces from a single 2D drawing traced and annotated over a side-view photo of a partially symmetrical object. Our reconstruction algorithm combines symmetry and orthogonality shapes cues within a unified optimization framework that solves for the 3D position of the Bezier control points of the drawn curves while being tolerant to drawing inaccuracy and perspective distortions. We then rely on existing surface optimization methods to produce a developable surface that interpolates our 3D curves. Our method is particularly well suited for the modeling and fabrication of fashion items as it converts the input drawing into flattened developable patterns ready for sewing.

We propose a new approach for detecting repeated patterns on a grid in a single image. To do so, we detect repetitions in the space of pre-trained deep CNN filter responses at all layer levels. These encode features at several conceptual levels (from low-level patches to high-level semantics) as well as scales (from local to global). As a result, our method is robust to challenging examples where repeated tiles show strong variation in appearance due to occlusions, lighting or background clutter. Our method contrasts with previous approaches that rely on keypoint extraction, description and clustering or on patch correlation. They generally only detect low-level feature clusters that do not handle complex pattern variations very well.
Our method incorporates high level features implicitly. As shown across all experiments, it is simpler, faster and more robust.

We propose a method to remove objects such as people and cars from multi-view urban image datasets, enabling free-viewpoint Image-Based Rendering (IBR) in the edited scenes. Our method combines information from multi-view 3D reconstruction with image inpainting techniques, by formulating the problem as an optimization of a global patch-based objective function. We use IBR techniques to reproject information from neighboring views, and 3D multi-view stereo reconstruction to perform multi-view coherent initialization for inpainting of pixels not filled by reprojection. Our algorithm performs multi-view consistent inpainting for color and 3D by blending reprojections with patch-based image inpainting. We run our algorithm on casually captured datasets, and Google Street View data, removing objects such as cars, people and pillars, showing that our approach produces results of sufficient quality for free-viewpoint IBR on “cleaned up” scenes, as well as IBR scene editing, such as limited displacement of real objects.

With hardware tessellation, highly detailed geometric models are decomposed into patches whose tessellation factor can be specified dynamically and independently at rendering time to control polygon resolution. Yet, to achieve maximum efficiency, an appropriate factor needs to be selected for each patch according to its content (geometry and appearance) and the current viewpoint distance and orientation. We propose a novel patch-based error metric that addresses this problem. It summarizes both the geometrical error and the texture parametrization deviation of a simplified patch compared to the corresponding detailed surface. This metric is compact and can be efficiently evaluated on the GPU along any view direction.

Recent surface acquisition technologies based on microsensors produce three-space tangential curve data which can be transformed into a network of space curves with surface normals. This paper addresses the problem of surfacing an arbitrary closed 3D curve network with given surface normals. Thanks to the normal vector input, the patch finding problem can be solved unambiguously and an initial piecewise smooth triangle mesh is computed. The input normals are propagated throughout the mesh. Together with the initial mesh, the propagated normals are used to compute mean curvature vectors. We then compute the final mesh as the solution of a new variational optimization method based on the mean curvature vectors. The intuition behind this original approach is to guide the standard Laplacian-based variational methods by the curvature information extracted from the input normals. The normal input increases shape fidelity and allows to achieve globally smooth and visually pleasing shapes.

Pretend play is a storytelling technique, naturally used from very young ages, which relies on object substitution to represent the characters of the imagined story. We propose "Make-believe", a system which assists the storyteller by generating a virtualized story from a recorded dialogue performed with 3D printed figurines. We capture the gestures and facial expressions of the storyteller using Kinect cameras and IMU sensors and transfer them to their virtual counterparts in the story-world. As a proof-of-concept, we demonstrate our system with an improvised story involving a prince and a witch, which was successfully recorded and transferred into 3D animation.

In this work, we present a new direct approach to reconstruct 3D models of objects in the form of homogeneous, circular generalized cylinders, featuring a planar axis. The input of the proposed method is a single image on which the user strokes guide the modeling process with a user selected prior. The main idea is the combination of human perception (via user strokes) with the computational power (reconstructing the 3D circle sections constituting the generalized cylinders). The proposed method is then successfully applied to generate models of objects in the public spaces (e.g. lamp posts, tree trunks, and pipes).

This paper focuses on the simulation of colloidal suspensions on the GPU for soft matter applications, where solvent particles (usually water) interact with bigger, solid particles. Our implementation is based on a coarse-grained model for the solvent named Stochastic Rotation Dynamics (SRD), also known as multi-particle collision dynamics (MPCD). We introduce explicit repulsive interactions between the solute and the solvent particles which are chosen to avoid depletion and to mimic lubrication phenomena. This method, called force coupling is computationally expensive for large systems but we show here how it can be adapted for calculations on graphical processing units (GPU).

Structure and Appearance Optimization for Controllable Shape Design

Jonàs Martínez1, Jérémie Dumas1,2, Sylvain Lefebvre1, Li-Yi Wei3

1 INRIA, 2 Université de Lorraine,3 University of Hong Kong

Papier déjà publié | SIGGRAPH Asia 2015

The field of topology optimization seeks to optimize shapes under structural objectives, such as achieving the most rigid shape using a given quantity of material. Besides optimal shape design, these methods are increasingly popular as design tools, since they automatically produce structures having desirable physical properties, a task hard to perform by hand even for skilled designers. However, there is no simple way to control the appearance of the generated objects.
In this paper, we propose to optimize shapes for both their structural properties and their appearance, the latter being controlled by a user-provided pattern example. These two objectives are challenging to combine, as optimal structural properties fully define the shape, leaving no degrees of free dom for appearance. We propose a new formulation where appearance is optimized as an objective while structural properties serve as constraints. This produces shapes with sufficient rigidity while allowing enough freedom for the appearance of the final structure to resemble the input exemplar.
Our approach generates rigid shapes using a specified quantity of material while observing optional constraints such as voids, fills, attachment points, and external forces. The appearance is defined by examples, making our technique accessible to casual users. We demonstrate its use in the context of fabrication using a laser cutter to manufacture real objects from optimized shapes.